Artificial intelligence

Gartner expects that by 2023, one-third of companies that have implemented IoT will also have implemented AI in conjunction with at least one IoT project. The popularity and intrigue in AI show no signs of slowing down, with it being named one of the 5 biggest tech trends this year. We support our customers by integrating AI into their products, which in turn, pushes their products to new technological heights and generates invaluable data to improve future work.

Thaumatec can help you be at the forefront of the AI revolution. We can support your company throughout the entire process: from the initial conception to solution development and production.


Chief Technology Officer

Contact me to talk about AI!


Computer vision: object detection, semantic segmentation, image generation; techniques: various architectures of CNN, GAN, transfer learning, autoencoders, TensorFlow, TensorFlow Lite;

• Natural Language Processing: speech recognition, NL understanding like text summarization, topic modelling or sentiment analysis; techniques: TFiDF, Word2Vec, BERT, GPT-3 and many more.

• Predictive modeling: time series forecasting, classification, regression; techniques: ARIMA, regressions, random forests, Xgboost, deep learning, and many more.

• Optimization: Genetic Algorithms, Bayesian Optimization;

• Recommendation engines: collaborative, content based, hybrids.

• Anomalies detection: clustering, dimensionality reduction, isolation forests.

• Simulations: Monte-Carlo, reinforcement learning.

• Software development: Python (Pandas, NumPy, Scikit-learn), R;

• Data Visualization (Matplotlib, Bokeh, Tableau, d3).

• All kind of databases (sql, nosql), data warehouses (cloud, on-premises), data lakes and data transformation tools;

• Cloud IoT tool stacks: Azure IoT Hub, AWS IoT Core;

• Big data tool stack: Hadoop, Kafka, HDInsights, Spark, Dask;

• Software development in general (Python).

• ML models training and operationalisation: Azure Machine Learning Studio, Amazon SageMaker;

• Devops tooling: CI/CD tools, Docker, Kubernetes;

• Software development in general (Python).


  • AI Consulting – we can help you explore the “art of the possible”

  • Data Engineering – extracting, transforming, cleaning, joining and loading the data from various sources

  • Machine Learning and Statistical Modelling – computer vision, forecasting, recommendation engines, anomalies detection, reinforcement learning, optimization, simulations

  • Model operationalization – deployment and monitoring in the cloud and on the edge

  • Data visualization – the fastest path to learning from the data is the proper visualization


1. Immersion
The main goal of this phase is to achieve a common understating between the customer and the data science team. The first step is to help the team to understand the business domain. Next, the detailed definition of what goals the model is to achieve needs to be agreed – the use case is to be specified. With this, the team needs to review the available data sets – quantity and quality. Finally, the scope for the Proof of Data is chosen, with expected accuracy.

2. Proof of Data
The main goal of this phase is the use case feasibility. With Data Science, usually the most important aspect to verify is weather the data is good enough to produce an accurate enough model. The approach is to choose a small part of the problem, initially clean the data and apply a small subset of standard models. The result is next analysed and the decision about the path of continuation is agreed with the customer.

3. Delivery
The delivery phase of a data science project is highly iterative. (It is based on the common standard CRISP-DM). Understanding of the business domain and data sets of the modelled aspect allows to start the data cleaning (preparation). The prepared data allow to train initial models. Looking at the models accuracy allows the team to understand potential issues in the data and results in more data cleaning. After multiple iterations, the results are evaluated with the customer. This usually provides to better understanding of the business and data set, allowing for creation of the next iteration of models. This cycle repeats until the accuracy achieve the acceptable level and can be deployed (operationalised) into a working solution.

4. Maintenance
Once deployed, the model needs to be monitored. Often, the accuracy of the model degrades with time, which is the result of the introduction of the new types of input data (not known when the model was trained) and the shifts of the business process that is modelled. Additionally, the working model could benefit from feedback loops or other data that can be started to gather after deployment. A common practise is to re-train the models recurrently (or when the accuracy drops below a given threshold) and to re-design them occasionally.


Data modelling

CNN, TensorFlow, TFiDF, Word2Vex, XgBoost, ARIMA, Clustering, Isolation forests, Python, Scikit learn, R

Data engineering

Azure IoT Hub, AWS IoT Core, SQL, noSQL, Azure ML Studio, Hadoop, Kafka, Docker, Kubernetes

read case studies

Smart healthcare

​Smart healthcare is one of the toughest but also fastest growing industries. A Silicon Valley start-up with a strong background in medical surgery and Thaumatec…
read more

Smart streetlight system

The City of Amsterdam has been very actively engaged in smart city development. Upgrading the street lighting infrastructure with new technology was high on the…
read more

Mobile LoRa gateway

Thaumatec built the solar-powered Lora Gateway because we believe, that this device can solve a lot of global problems and help many businesses.
read more

Wrocław the smart(est) city

Thaumatec has a strong partnership with top-class universities like Wrocław University of Technology and Science and the most respected business networks like DSP Valley from…
read more

Smart robot for elderly care

​AI is the most exciting field ever, especially since the creation of robots. Thaumatec was lucky (and qualified) to be assigned to work on a…
read more

Smart sleep tracker

The consequences of sleeping deprivation can affect many, so a solution was formed for this problem and Thaumatec helped in the making. Read our story…
read more

LoRa Communication Module for Drones

LoRa communication module for drones Lora is one of the most promising IoT technologies that deliver communication for areas where availability of power grid is…
read more

Biometric identity

Biometric identity products deliver effortless, fast, and highly accurate biometric enrollment and identification. Designed for high throughput identification and verification, in other words, these products…
read more

Smart security system

Hago Next, a cleaning company that provides services to public places like train stops, was searching for the ideal partner to provide them with IoT…
read more

Do you need a help with choosing a service?

Contact us, we'll help you.

Contact us


absl it_corner polish_netherlands_chamber_of_commerce politechnika_wroclawska polish_chamber_of_commerce_in_the_netherlands
Copyrights © Thaumatec 2022